Behavioral Player Matching in Multi-User Online Games
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Solution Overview
Problem
Current multi-user online gaming systems fail to accurately match players based on their behavioral data, leading to unpredictable gaming experiences, as existing systems rely on skill level and experience, which do not guarantee compatibility or enjoyment.
Innovation Solution
An online multi-user game system that includes a user profile database storing behavioral data and a player matching server that matches users based on behavioral characteristics, such as friendliness, helpfulness, and team orientation, in addition to skill and experience levels, to form compatible teams and opponents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If players are matched randomly or based solely on skill level, then the matching process is simple and fast, but the gaming experience becomes unpredictable and less enjoyable
Solution Approach 1:
The player profile is segmented into multiple dimension attributes including skill level, experience level, and behavioral characteristics. The matching system processes each dimension separately and combines the results to create comprehensive player matches, allowing complex matching logic to be broken down into manageable components that can be processed efficiently
Solution Approach 2:
The system adds a new dimension of behavioral characteristics to the traditional skill-based matching approach. By incorporating dimensions such as teamwork orientation, communication style, and in-game behavior patterns, the system creates a multi-dimensional matching framework that produces more reliable gaming experiences while maintaining acceptable system complexity through structured data organization
2Reliability
If player matching considers multiple factors including behavioral data, then player compatibility improves, but data collection and processing requirements increase
Solution Approach 1:
Player behavioral characteristics and preferences are collected and stored in advance during the matchmaking waiting period. This preliminary data collection allows the actual game matching to proceed quickly without needing to gather information in real-time, reducing the information processing burden during critical matching operations while still achieving high player compatibility
Solution Approach 2:
Instead of processing raw behavioral data in its original complex form during matching, the system creates simplified profile representations that capture essential matching characteristics. These copied summary profiles enable fast comparison and matching operations while preserving the necessary information about player compatibility without the overhead of processing complete raw data sets
Data Source
AI summary
The field of the invention relates to multi-user online gaming systems, and more particularly to systems and methods that enable a spectator's experience for online active games. In a preferred embodiment, an online multiuser game system includes a user matching system configured to match users for a game session, wherein the user matching system is enabled to match a first user with another user based at least in part on behavior data in the first user's profile.